Practical Velocity Tracking Control of a Parallel Robot Based on Fuzzy Adaptive Algorithm

Abstract

Due to the advantages of its compact structure and high operation accuracy, the six degrees of freedom (6-DOF) parallel platform has been widely used as a carrier of medical rehabilitation devices. Fuzzy adaptive algorithm does not depend on the mathematical model of controlled object, which possesses good nonlinear characteristics. Those entire features make it an effective method to control such complex and coupling platforms. To facilitate the application of robotics in lower limb rehabilitation fields, a robotic system in practical environment was established based on kinematics modeling of the 6-DOF Stewart-based platform. In order to improve the velocity tracking accuracy, this paper proposed a closed-loop control strategy based on fuzzy adaptive algorithm. The velocity feedback information was utilized to modify the PID parameters adaptively in realtime through fuzzy inference units. Several experiments in practical environment were conducted, and the results demonstrated that the proposed algorithm could effectively reduce the speed jitter, enhance the position and velocity tracking precision of the robot, and the reliability and robustness of the system could also be ensured.